DocumentCode :
2141617
Title :
Detecting deception in testimony
Author :
Little, A. ; Skillicorn, D.B.
Author_Institution :
Sch. of Comput., Queen´´s Univ., Kingston, ON
fYear :
2008
fDate :
17-20 June 2008
Firstpage :
13
Lastpage :
18
Abstract :
Several models for deception in text, based on changes in usage frequency of certain classes of words, have been proposed. These are empirically derived from settings in which individuals are asked to lie or be truthful in freeform text. We consider the problem of detecting deception in testimony, where the content generated must necessarily be responsive to questions, where there is the opportunity for immediate followup if the possibility of deception is detected by the questioner, and where those who have reasons to be deceptive have time and motivation to rehearse potential answers. Using the testimony to the Gomery Commission, a situation in which many witnesses had some motivation to be deceptive, we propose and validate a model for deception in testimony. We achieve substantial (80%) agreement with media estimates of who was motivated to testify in a deceptive way.
Keywords :
law administration; text analysis; Gomery Commission testimony; psychology; testimony deception detection; text analysis; Artificial intelligence; Frequency; Humans; Internet; Mutual information; Statistical analysis; Statistical distributions; Testing; Uniform resource locators; Yarn;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligence and Security Informatics, 2008. ISI 2008. IEEE International Conference on
Conference_Location :
Taipei
Print_ISBN :
978-1-4244-2414-6
Electronic_ISBN :
978-1-4244-2415-3
Type :
conf
DOI :
10.1109/ISI.2008.4565022
Filename :
4565022
Link To Document :
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